Dependency and Mutation Rate Figures
Neekesh Dharia & Guillaume Kugener
2020-08-18
Generated using: 20Q1
The table below highlights all of the cell lines that are included in the analyses and the types that they are annotated as:
Overview
- Calculate mutation rates / burden per cell line using multiple methods given fact that these historical cell lines do not have matched germline for somatic mutation calling
- Compare mutation rates to dependency rates
- Compare dependency rates to screen confounders (quality, Cas9 activity, etc)
COSMIC gene list
The list of COSMIC genes was downloaded from https://cancer.sanger.ac.uk/cosmic/census on 1/11/2020 selecting ‘both tiers’.
WES counts from MAF file
Mutation plot counting the total number of mutations we cell line using only WES data (from either Sanger or the Broad).
All WES
WES filtered for COSMIC genes
WES filtered for mutations in COSMIC genes
Number of selective dependencies for lines with WES
Mutation rates in COSMIC genes, pediatric vs other tumors
WGS counts from MAF file
Mutation plot counting the total number of mutations per cell line using only WGS data.
Starting from the DepMap mutations MAF file, filter for mutations that were called using WGS. Count the total number of mutations called in each sample and then plot the results. Sort sample by the median count by lineage.
All WGS
WGS filtered for COSMIC genes
WGS filtered for mutations in COSMIC genes
Number of selective dependencies for lines with WGS
Running MutSig
MutSig2CV was run on samples separately for MAFs for Broad WES, Sanger WES, and COSMIC only mutations. This was done by downloading MutSig2CV from https://software.broadinstitute.org/cancer/cga/sites/default/files/data/tools/mutsig/MutSig2CV.tar.gz. Following the README, this was installed along with the MCR in a VM running linux (VirtualBox 6.1.6 with 12GB RAM, Ubuntu 18.04.03 LTS).
MutSig2CV removes cell lines that appear to be duplicates (having almost identical mutational patterns) and then infers a mutation rate. These mutation rates were used for the plot below.
MutSig on all WES
MutSig on COSMIC genes
Recurrent mutations within pediatric cell lines vs adult cell lines
Overview of gene selection
MutSig2CV analyzes somatic point mutations discovered in DNA sequencing, identifying genes mutated more often than expected by chance given inferred background mutation processes. MutSig2CV consists of three independent statistical tests, described briefly below:
Abundance (CV): The most important step for inferring genes’ mutational significance is to properly classify whether the gene is highly mutated relative to some background mutation rate (BMR), which varies on a macroscopic level across patients and genes and on a microscopic level across sequence contexts. MutSig accounts for all three of these to renormalize BMR on a per-gene, -patient, and -context level.
Clustering (CL): Genes often harbor mutational hotspots, specific sites that are frequently mutated. While abundance calculations bin mutations on the gene level, clustering bins mutations on the local site level, which allows MutSig to differentiate between genes with uniformly distributed mutations and genes with localized hotspots, assigning higher significance to the latter.
Conservation (FN): MutSig uses evolutionary conservation as a proxy for determining the functional significance of a mutated site. It assumes that genetic sites highly conserved across vertebrates have greater functional significance than weakly conserved sites. MutSig assigns a higher significance to genes that experience frequent mutations in highly conserved sites.
Top mutated COSMIC genes in pediatric vs adult tumor types
In the plots below, we look only at the COSMIC genes and ignore any of the significance thresholds from MutSig2CV. The frequency of mutations in these genes is determined by counting the number of cell lines that had this mutation and normalizing to the total number of cell lines evaluated.
The table below outlines all of the genes that passed this criteria (hover over column names for meaning):
The plot below shows % of cell lines with a damaging, missense, or hotspot mutation in the given gene.
Top mutated genes in pediatric lines (MutSig COSMIC only)
Top mutated genes in adult lines (MutSig COSMIC)
Dependency and mutation rates vs confounders
Look at the relationship of dependency and mutation rate with NNMD (separation of positive and negative controls) and CAS9 activity (measured as % GFP remaining after CRISPR-Cas9 directed GFP editting, i.e. lower number indicates higher CAS9 activity).
Selective dependencies vs NNMD
WES mutation rate vs NNMD
MutSig2CV mutation rate vs NNMD
Selective dependencies vs Cas9
WES mutation rate vs Cas9
MutSig2CV mutation rate vs Cas9
Selective dependencies vs growth
WES mutation rate vs growth
MutSig2CV mutation rate vs growth
Dependency rate vs media
WES mutation rate vs media
MutSig2CV mutation rate vs media
Dependency rate vs primary/metastasis
WES mutation rate vs primary/metastasis
MutSig2CV mutation rate vs primary/metastasis
Selective dependencies vs treatment for pediatric tumors
WES mutation rate vs treatment for pediatric tumors
MutSig2CV mutation rate vs treatment for pediatric tumors
Selective dependencies vs expression outliers
WES mutation rate vs expression outliers
MutSig2CV mutation rate vs expression outliers
Estimating false positive rate
Non-expressed genes (TPM=0) with dep >0.5 per cell line
Non-expressed genes (TPM<0.5) with dep >0.5 per cell line
Non-expressed genes (TPM<1) with dep >0.5 per cell line
Session Info
devtools::session_info()## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
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## language (EN)
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## ctype en_US.UTF-8
## tz America/New_York
## date 2020-08-18
##
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